The recently proposed joint-optimized normalized least-mean-square (JO-NLMS) algorithm was developed in the context of a state variable model. Moreover, following the minimization of the system misalignment and using an iterative procedure for adjusting the system model parameter, this algorithm is able to achieve a proper compromise between the performance criteria (i.e., fast convergence/tracking and low misadjustment). In this paper, we present a performance analysis of the JO-NLMS algorithm, outlining some relations between its main parameters and indicating its good behavior.